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KazNERD: Kazakh Named Entity Recognition Dataset

arXiv 2111.13419 ↗First posted 26 Nov 2021cs.CL cs.IRcited by 15

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Abstract (arXiv)

We present the development of a dataset for Kazakh named entity recognition. The dataset was built as there is a clear need for publicly available annotated corpora in Kazakh, as well as annotation guidelines containing straightforward--but rigorous--rules and examples. The dataset annotation, based on the IOB2 scheme, was carried out on television news text by two native Kazakh speakers under the supervision of the first author. The resulting dataset contains 112,702 sentences and 136,333 annotations for 25 entity classes. State-of-the-art machine learning models to automatise Kazakh named entity recognition were also built, with the best-performing model achieving an exact match F1-score of 97.22% on the test set. The annotated dataset, guidelines, and codes used to train the models are freely available for download under the CC BY 4.0 licence from https://github.com/IS2AI/KazNERD.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 11 of its 41 references that are in the map. First posted on arXiv 26 Nov 2021.

Builds on

11 of 41 references.

References · 11

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  3. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  4. 2016End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRFcited by 341
  5. 2020A Crowdsourced Open-Source Kazakh Speech Corpus and Initial Speech Recognition Baselinecited by 14
  6. 2021KazakhTTS: An Open-Source Kazakh Text-to-Speech Synthesis Datasetcited by 13
  7. 2019Introducing RONEC -- the Romanian Named Entity Corpuscited by 12
  8. 2019Attending to Entities for Better Text Understandingcited by 6
  9. 2020A Corpus Study and Annotation Schema for Named Entity Recognition and Relation Extraction of Business Productscited by 5
  10. 2021A Study of Multilingual End-to-End Speech Recognition for Kazakh, Russian, and Englishcited by 4
  11. 2020Neural Named Entity Recognition for Kazakhcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 1; 2024: 7; 2025: 4; 2026: 2.

15 papers.

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  1. 2022KazakhTTS2: Extending the Open-Source Kazakh TTS Corpus With More Data, Speakers, and Topicscited by 10
  2. 2024Sebastian, Basti, Wastl?! Recognizing Named Entities in Bavarian Dialectal Datacited by 8
  3. 2024KazQAD: Kazakh Open-Domain Question Answering Datasetcited by 7
  4. 2024Recent Advancements and Challenges of Turkic Central Asian Language Processingcited by 6
  5. 2024KazSAnDRA: Kazakh Sentiment Analysis Dataset of Reviews and Attitudescited by 5
  6. 2024KazParC: Kazakh Parallel Corpus for Machine Translationcited by 5
  7. 2025KazMMLU: Evaluating Language Models on Kazakh, Russian, and Regional Knowledge of Kazakhstancited by 5
  8. 2025Instruction Tuning on Public Government and Cultural Data for Low-Resource Language: a Case Study in Kazakhcited by 4
  9. 2025Sherkala-Chat: Building a State-of-the-Art LLM for Kazakh in a Moderately Resourced Settingcited by 3
  10. 2023Multilingual Text-to-Speech Synthesis for Turkic Languages Using Transliterationcited by 2
  11. 2024OpenNER 1.0: Standardized Open-Access Named Entity Recognition Datasets in 50+ Languagescited by 2
  12. 2026SozKZ: Training Efficient Small Language Models for Kazakh from Scratchcited by 2
3 more
  1. 2025Human-Annotated NER Dataset for the Kyrgyz Languagecited by 1
  2. 2026TurkicNLP: An NLP Toolkit for Turkic Languagescited by 1
  3. 2024CO-Fun: A German Dataset on Company Outsourcing in Fund Prospectuses for Named Entity Recognition and Relation Extractioncited by 0